Market Competitiveness, Policy & Behavioral Simulation

The ultimate goal of management is to steer businesses and organizations towards better strategic outcomes. Business strategies are defined to elevate businesses to positions resulting in for instance better performance, higher revenues or higher market footprint. A multitude of goals ought to be addressed to ensure that organizations secure their survival in a broader competitive landscape. In competitive market environment, the survival of the business is governed by natural selection. Evolutionary laws will only allow the survival of the fittest that are able to define and apply strategies capable of moving the organizations to stronger competitive positions. This dissertation strives to propose innovative methodology to studying business competitiveness. Businesses operate in constantly changing, extremely challenging and hyper-competitive environment as an effect of ongoing globalization, increasing role of innovations and the rapid introduction of new technologies. Moreover, the market environment will always posses some specific characteristics, further increasing its coplexity and dynamic nature - irrationality, subjectivity, and being an open system, to name a few. This thesis strives to introduce new computational methodology for studying market and business competitiveness and its driving factors. The innovation resides in detailed modeling of company internal structures and processes and their direct dynamic integration with decentralized model of market behavior. Through this framework, managerial decisions are dynamically projected to the corresponding market and, vice-versa, market responses can be continuously anticipated and instantly processed inside the company. Its aims is to define and evaluate experimental methodology to studying emergence of customer value in the market place and of the factors positively affecting the value creation process, thus defining and providing a computational approach for studying market competitiveness. This dissertation discusses the existing quantitative and qualitative approaches and suggests experimental methods capable of providing further insights into the research domain.